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Second-line Treatments for Advanced Gastric Cancer: A Network Meta-Analysis of Overall Survival Using Parametric Modelling Methods

Second-line Treatments for Advanced Gastric Cancer: A Network Meta-Analysis of Overall Survival... Oncol Ther (2017) 5:53–67 DOI 10.1007/s40487-017-0048-0 ORIGINAL RESEARCH Second-line Treatments for Advanced Gastric Cancer: A Network Meta-Analysis of Overall Survival Using Parametric Modelling Methods Rebecca C. Harvey Received: April 10, 2017 / Published online: June 6, 2017 The Author(s) 2017. This article is an open access publication availability of Kaplan–Meier curves for overall ABSTRACT survival. Individual patient data (IPD) were recreated using digitisation software along with Introduction: Advanced gastric cancer (AGC) is a published algorithm in R. The data were one of the most common forms of cancer and analysed using multi-dimensional network remains difficult to cure. There is currently no meta-analysis (NMA) methods. A series of recommended therapy for second-line AGC in parametric models were fitted to the pseu- the UK despite the availability of various inter- do-IPD. Both fixed and random-effects models ventions. This paper aims to compare different were fitted to explore long-term survival pro- interventions for treatment of second-line AGC spects based on extrapolation methods and using more complex methods to estimate rela- estimated mean survival. tive efficacy, fitting various parametric models Results: Relative efficacy estimates were and to compare results to those published compared to those previously reported, which adopting conventional methods of synthesis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Oncology and Therapy Springer Journals

Second-line Treatments for Advanced Gastric Cancer: A Network Meta-Analysis of Overall Survival Using Parametric Modelling Methods

Oncology and Therapy , Volume 5 (1) – Jun 6, 2017

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Publisher
Springer Journals
Copyright
Copyright © 2017 by The Author(s)
Subject
Medicine & Public Health; Internal Medicine
ISSN
2366-1070
eISSN
2366-1089
DOI
10.1007/s40487-017-0048-0
Publisher site
See Article on Publisher Site

Abstract

Oncol Ther (2017) 5:53–67 DOI 10.1007/s40487-017-0048-0 ORIGINAL RESEARCH Second-line Treatments for Advanced Gastric Cancer: A Network Meta-Analysis of Overall Survival Using Parametric Modelling Methods Rebecca C. Harvey Received: April 10, 2017 / Published online: June 6, 2017 The Author(s) 2017. This article is an open access publication availability of Kaplan–Meier curves for overall ABSTRACT survival. Individual patient data (IPD) were recreated using digitisation software along with Introduction: Advanced gastric cancer (AGC) is a published algorithm in R. The data were one of the most common forms of cancer and analysed using multi-dimensional network remains difficult to cure. There is currently no meta-analysis (NMA) methods. A series of recommended therapy for second-line AGC in parametric models were fitted to the pseu- the UK despite the availability of various inter- do-IPD. Both fixed and random-effects models ventions. This paper aims to compare different were fitted to explore long-term survival pro- interventions for treatment of second-line AGC spects based on extrapolation methods and using more complex methods to estimate rela- estimated mean survival. tive efficacy, fitting various parametric models Results: Relative efficacy estimates were and to compare results to those published compared to those previously reported, which adopting conventional methods of synthesis.

Journal

Oncology and TherapySpringer Journals

Published: Jun 6, 2017

References